You'll have to ask your doctor why there is no wearable technology in their stroke hospital.
Laziness? Incompetence? Or just don't care? No leadership? No strategy? Not my job?
Not knowing about it is a fireable reason.
- wearable (14)
- wearable arms (1)
- wearable computing (3)
- wearable devices (31)
- Wearable inertial measurement units (1)
- wearable sensors (10)
Wearable technology in stroke rehabilitation: towards improved diagnosis and treatment of upper-limb motor impairment
Abstract
Stroke
is one of the main causes of long-term disability worldwide, placing a
large burden on individuals and society. Rehabilitation after stroke
consists of an iterative process involving assessments and specialized
training, aspects often constrained by limited resources of healthcare
centers. Wearable technology has the potential to objectively assess and
monitor patients inside and outside clinical environments, enabling a
more detailed evaluation of the impairment and allowing the
individualization of rehabilitation therapies. The present review aims
to provide an overview of wearable sensors used in stroke rehabilitation
research, with a particular focus on the upper extremity. We summarize
results obtained by current research using a variety of wearable sensors
and use them to critically discuss challenges and opportunities in the
ongoing effort towards reliable and accessible tools for stroke
rehabilitation. Finally, suggestions concerning data acquisition and
processing to guide future studies performed by clinicians and engineers
alike are provided.
Introduction
Stroke is one of the leading causes of disability worldwide [1], with a global prevalence estimated at 42.4 million in 2015 [2]. Stroke results in permanent motor disabilities in 80% of cases [3]. During the acute and subacute stages (< 6 months after stroke [4]),
patients receive rehabilitation therapies at specialized healthcare
centers, consisting of an iterative process involving impairment
assessments, goal definition, intervention, and progress evaluation [5].
After being discharged from the rehabilitation center (i.e. after
entering the chronic stage, e.g., 6 months after stroke), 65% of
patients are unable to integrate affected limbs into everyday-life
activities [6],
showing a need for further treatment. Phrased differently, the
rehabilitative process after stroke depends on the effective assessment
of motor deficit and congruent allocation to treatment (diagnostics),
accurate appraisal of treatment effects (recovery/adaptation
evaluation), and prolonged treatment for continuous recovery during the
chronic stage (extended training).
Each of these three aspects present practical challenges. Assigned treatments depend on the assessed early-stage disability [3]. A variety of assessment scales exist to evaluate motor impairment after stroke, designed to capture aspects such as joint range of motion (ROM), synergistic execution of movements, reaching and grasping capabilities, object manipulation, etc. [7]. These assessments are normally applied by specialized medical personnel, which entails certain variability between assessments [8]. Besides consistency in repeated measurements, some scales like the Fugl-Meyer assessment (FMA) [9], are unable to capture the entire spectrum of motor function in patients due to limited sensitivity or ceiling effects [10].
In addition to thorough standardized assessment scales, progress in patients is observable during the execution of activities of daily living (e.g., during occupational therapy sessions). Nevertheless, task completion not always reflects recovery, as patients often adopt different synergistic patterns to compensate for lost function [11], and such behavior is not always evident.
Main provision of rehabilitation therapies occurs at hospitals and rehabilitation centers. Evidence of enhanced recovery related to more extensive training has been found [12], but limited resources at these facilities often obstruct extended care during the chronic stage. This calls for new therapeutic options allowing patients to train intensively and extensively after leaving the treatment center, while ensuring the treatment’s quality, effectiveness and safety.
Wearable sensors used during regular assessments can reduce evaluation times and provide objective, quantifiable data on the patients’ capabilities, complementing the expert yet subjective judgement of healthcare specialists. These recordings are more objective and replicable than regular observations. They have the potential of reducing diagnostic errors affecting the choice for therapies and their eventual readjustment. Additional information (e.g., muscle activity) extracted during the execution of multiple tasks can be used to better characterize motor function in patients, allowing for finer stratification into more specific groups, which can then lead to better targeted care (i.e. personalized therapies). These devices also make it possible to acquire data unobtrusively and continuously, which enables the study of motor function while patients perform daily-life activities. Further, the prospect of remotely acquiring data shows promise in the implementation of independent rehabilitative training outside clinics, allowing patients to work more extensively towards recovery.
The objective of this review is to provide an overview of wearable sensors used in stroke rehabilitation research, with a particular focus on the upper extremity, aiming to present a roadmap for translating these technologies from “bench to bedside”. We selected articles based on their reports about tests conducted with actual stroke patients, with the exception of conductive elastomer sensors, on which extensive research exists without tests in patients. In the section “Wearable devices used in stroke patients”, we summarize results obtained by current research using a variety of wearable sensors and use them to critically discuss challenges and opportunities in the ongoing effort towards reliable and accessible tools for stroke rehabilitation. In the “Discussion” section, we present suggestions concerning data acquisition and processing, as well as opportunities arising in this field, to guide future studies performed by clinicians and engineers alike.
Each of these three aspects present practical challenges. Assigned treatments depend on the assessed early-stage disability [3]. A variety of assessment scales exist to evaluate motor impairment after stroke, designed to capture aspects such as joint range of motion (ROM), synergistic execution of movements, reaching and grasping capabilities, object manipulation, etc. [7]. These assessments are normally applied by specialized medical personnel, which entails certain variability between assessments [8]. Besides consistency in repeated measurements, some scales like the Fugl-Meyer assessment (FMA) [9], are unable to capture the entire spectrum of motor function in patients due to limited sensitivity or ceiling effects [10].
In addition to thorough standardized assessment scales, progress in patients is observable during the execution of activities of daily living (e.g., during occupational therapy sessions). Nevertheless, task completion not always reflects recovery, as patients often adopt different synergistic patterns to compensate for lost function [11], and such behavior is not always evident.
Main provision of rehabilitation therapies occurs at hospitals and rehabilitation centers. Evidence of enhanced recovery related to more extensive training has been found [12], but limited resources at these facilities often obstruct extended care during the chronic stage. This calls for new therapeutic options allowing patients to train intensively and extensively after leaving the treatment center, while ensuring the treatment’s quality, effectiveness and safety.
Wearable sensors used during regular assessments can reduce evaluation times and provide objective, quantifiable data on the patients’ capabilities, complementing the expert yet subjective judgement of healthcare specialists. These recordings are more objective and replicable than regular observations. They have the potential of reducing diagnostic errors affecting the choice for therapies and their eventual readjustment. Additional information (e.g., muscle activity) extracted during the execution of multiple tasks can be used to better characterize motor function in patients, allowing for finer stratification into more specific groups, which can then lead to better targeted care (i.e. personalized therapies). These devices also make it possible to acquire data unobtrusively and continuously, which enables the study of motor function while patients perform daily-life activities. Further, the prospect of remotely acquiring data shows promise in the implementation of independent rehabilitative training outside clinics, allowing patients to work more extensively towards recovery.
The objective of this review is to provide an overview of wearable sensors used in stroke rehabilitation research, with a particular focus on the upper extremity, aiming to present a roadmap for translating these technologies from “bench to bedside”. We selected articles based on their reports about tests conducted with actual stroke patients, with the exception of conductive elastomer sensors, on which extensive research exists without tests in patients. In the section “Wearable devices used in stroke patients”, we summarize results obtained by current research using a variety of wearable sensors and use them to critically discuss challenges and opportunities in the ongoing effort towards reliable and accessible tools for stroke rehabilitation. In the “Discussion” section, we present suggestions concerning data acquisition and processing, as well as opportunities arising in this field, to guide future studies performed by clinicians and engineers alike.
More at link.
No comments:
Post a Comment